_base_ = "./fovea_r50_fpn_4x4_1x_coco.py"
model = dict(
    bbox_head=dict(
        with_deform=True, norm_cfg=dict(type="GN", num_groups=32, requires_grad=True)
    )
)
# learning policy
lr_config = dict(step=[16, 22])
runner = dict(type="EpochBasedRunner", max_epochs=24)
optimizer_config = dict(_delete_=True, grad_clip=dict(max_norm=35, norm_type=2))
